{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T19:24:55Z","timestamp":1769973895431,"version":"3.49.0"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2022,4,7]],"date-time":"2022-04-07T00:00:00Z","timestamp":1649289600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,4,7]],"date-time":"2022-04-07T00:00:00Z","timestamp":1649289600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2022,5]]},"DOI":"10.1007\/s10115-022-01674-9","type":"journal-article","created":{"date-parts":[[2022,4,7]],"date-time":"2022-04-07T03:56:47Z","timestamp":1649303807000},"page":"1349-1384","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Modeling and predicting students\u2019 engagement behaviors using mixture Markov models"],"prefix":"10.1007","volume":"64","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4620-4362","authenticated-orcid":false,"given":"Rabia","family":"Maqsood","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4519-0173","authenticated-orcid":false,"given":"Paolo","family":"Ceravolo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4180-4948","authenticated-orcid":false,"given":"Crist\u00f3bal","family":"Romero","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4216-6378","authenticated-orcid":false,"given":"Sebasti\u00e1n","family":"Ventura","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,4,7]]},"reference":[{"key":"1674_CR1","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/978-1-4612-1694-0_15","volume-title":"Selected papers of Hirotugu Akaike","author":"H Akaike","year":"1998","unstructured":"Akaike H (1998) Information theory and an extension of the maximum likelihood principle. Selected papers of Hirotugu Akaike. Springer, Berlin, pp 199\u2013213"},{"key":"1674_CR2","unstructured":"Anderson E (2017) Measurement of online student engagement: Utilization of continuous online student behaviors as items in a partial credit Rasch model. PhD thesis, Morgridge College of Education, University of Denver, USA, Electronic Theses and Dissertations. 1248"},{"key":"1674_CR3","unstructured":"Beal CR, Qu L, Lee H (2006) Classifying learner engagement through integration of multiple data sources. In: AAAI, pp 151\u2013156"},{"key":"1674_CR4","unstructured":"Beal C, Mitra S, Cohen P (2007) Modeling learning patterns of students with a tutoring system using hidden Markov model. In: Luckin R et al (eds) Proceedings of the 13th international conference on Artificial intelligence in education (AIED). Marina del Rey"},{"issue":"3\u20134","key":"1674_CR5","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1016\/S0167-9473(02)00163-9","volume":"41","author":"C Biernacki","year":"2003","unstructured":"Biernacki C, Celeux G, Govaert G (2003) Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate gaussian mixture models. Comput Stat Data Anal 41(3\u20134):561\u2013575","journal-title":"Comput Stat Data Anal"},{"key":"1674_CR6","doi-asserted-by":"crossref","unstructured":"Boroujeni MS, Dillenbourg P (2018) Discovery and temporal analysis of latent study patterns in MOOC interaction sequences. In: Proceedings of the 8th international conference on learning analytics and knowledge. ACM, pp 206\u2013215","DOI":"10.1145\/3170358.3170388"},{"key":"1674_CR7","unstructured":"Botelho AF, Baker RS, Heffernan NT (2019) Machine-learned or expert-engineered features? Exploring feature engineering methods in detectors of student behavior and affect. In: The twelfth international conference on educational data mining"},{"issue":"1","key":"1674_CR8","first-page":"104","volume":"5","author":"F Bouchet","year":"2013","unstructured":"Bouchet F, Harley JM, Trevors GJ, Azevedo R (2013) Clustering and profiling students according to their interactions with an intelligent tutoring system fostering self-regulated learning. JEDM J Educ Data Min 5(1):104\u2013146","journal-title":"JEDM J Educ Data Min"},{"issue":"5","key":"1674_CR9","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1007\/s11257-014-9150-2","volume":"24","author":"P Bouvier","year":"2014","unstructured":"Bouvier P, Sehaba K, Lavou\u00e9 \u00c9 (2014) A trace-based approach to identifying users\u2019 engagement and qualifying their engaged-behaviours in interactive systems: application to a social game. User Model User Adapt Interact 24(5):413\u2013451","journal-title":"User Model User Adapt Interact"},{"key":"1674_CR10","unstructured":"Brown LN, Howard AM (2014) A real-time model to assess student engagement during interaction with intelligent educational agents. In: 2014 ASEE annual conference & exposition, pp 24\u201395"},{"issue":"4","key":"1674_CR11","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1023\/A:1024992613384","volume":"7","author":"I Cadez","year":"2003","unstructured":"Cadez I, Heckerman D, Meek C et al (2003) Model-based clustering and visualization of navigation patterns on a web site. Data Min Knowl Discov 7(4):399\u2013424","journal-title":"Data Min Knowl Discov"},{"issue":"13","key":"1674_CR12","first-page":"1","volume":"8","author":"E Chapman","year":"2003","unstructured":"Chapman E (2003) Alternative approaches to assessing student engagement rates. Pract Assess 8(13):1\u20137","journal-title":"Pract Assess"},{"key":"1674_CR13","unstructured":"Charrad M, Ghazzali N, Boiteau V, Niknafs A (2012) Nbclust package: finding the relevant number of clusters in a dataset. UseR! 2012"},{"key":"1674_CR14","first-page":"14","volume-title":"European conference on technology enhanced learning","author":"M Cocea","year":"2007","unstructured":"Cocea M, Weibelzahl S (2007) Cross-system validation of engagement prediction from log files. European conference on technology enhanced learning. Springer, Berlin, pp 14\u201325"},{"issue":"4","key":"1674_CR15","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1007\/s11257-009-9065-5","volume":"19","author":"M Cocea","year":"2009","unstructured":"Cocea M, Weibelzahl S (2009) Log file analysis for disengagement detection in e-learning environments. User Model User Adapt Interact 19(4):341\u2013385","journal-title":"User Model User Adapt Interact"},{"issue":"2","key":"1674_CR16","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1109\/TLT.2010.14","volume":"4","author":"M Cocea","year":"2011","unstructured":"Cocea M, Weibelzahl S (2011) Disengagement detection in online learning: Validation studies and perspectives. IEEE Trans Learn Technol 4(2):114\u2013124","journal-title":"IEEE Trans Learn Technol"},{"issue":"1","key":"1674_CR17","first-page":"31","volume":"3","author":"PR Cohen","year":"2009","unstructured":"Cohen PR, Beal CR (2009) Temporal data mining for educational applications. Int J Softw Inform 3(1):31\u201346","journal-title":"Int J Softw Inform"},{"issue":"2","key":"1674_CR18","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1037\/0003-066X.60.2.170","volume":"60","author":"G Cumming","year":"2005","unstructured":"Cumming G, Finch S (2005) Inference by eye: confidence intervals and how to read pictures of data. Am Psychol 60(2):170","journal-title":"Am Psychol"},{"issue":"1","key":"1674_CR19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.2517-6161.1977.tb01600.x","volume":"39","author":"AP Dempster","year":"1977","unstructured":"Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B (Methodol) 39(1):1\u201322","journal-title":"J R Stat Soc Ser B (Methodol)"},{"issue":"1\u20132","key":"1674_CR20","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1007\/s11257-011-9106-8","volume":"22","author":"MC Desmarais","year":"2012","unstructured":"Desmarais MC, Baker RS (2012) A review of recent advances in learner and skill modeling in intelligent learning environments. User Model User Adapt Interact 22(1\u20132):9\u201338","journal-title":"User Model User Adapt Interact"},{"key":"1674_CR21","doi-asserted-by":"crossref","unstructured":"Dziak JJ, Coffman DL, Lanza ST et al (2019) Sensitivity and specificity of information criteria. bioRxiv, p 449751","DOI":"10.1101\/449751"},{"key":"1674_CR22","doi-asserted-by":"crossref","unstructured":"Fok AW, Wong HS, Chen Y (2005) Hidden Markov model based characterization of content access patterns in an e-learning environment. In: 2005 IEEE international conference on multimedia and expo. IEEE, pp 201\u2013204","DOI":"10.1109\/ICME.2005.1521395"},{"issue":"1","key":"1674_CR23","doi-asserted-by":"publisher","first-page":"59","DOI":"10.3102\/00346543074001059","volume":"74","author":"JA Fredricks","year":"2004","unstructured":"Fredricks JA, Blumenfeld PC, Paris AH (2004) School engagement: potential of the concept, state of the evidence. Rev Educ Res 74(1):59\u2013109","journal-title":"Rev Educ Res"},{"key":"1674_CR24","unstructured":"Gardner-Medwin AR, Gahan M (2003) Formative and summative confidence-based assessment. Loughborough University"},{"key":"1674_CR25","doi-asserted-by":"crossref","unstructured":"Gupta MR, Chen Y et\u00a0al (2011) Theory and use of the EM algorithm. Found Trends\u00ae Signal Process 4(3):223\u2013296","DOI":"10.1561\/2000000034"},{"key":"1674_CR26","unstructured":"Hansen C, Hansen C, Hjuler N et al. (2017) Sequence modelling for analysing student interaction with educational systems. In: Proceedings of the 10th international conference on educational data mining (2017), pp 232\u2013237"},{"issue":"1","key":"1674_CR27","first-page":"197","volume":"5","author":"A Hershkovitz","year":"2009","unstructured":"Hershkovitz A, Nachmias R (2009) Learning about online learning processes and students\u2019 motivation through web usage mining. Interdiscip J E-Learning Learn Objects 5(1):197\u2013214","journal-title":"Interdiscip J E-Learning Learn Objects"},{"key":"1674_CR28","unstructured":"Hu Z (2015) Initializing the EM algorithm for data clustering and sub-population detection. PhD thesis, The Ohio State University"},{"issue":"3","key":"1674_CR29","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1023\/A:1009769707641","volume":"2","author":"Z Huang","year":"1998","unstructured":"Huang Z (1998) Extensions to the k-means algorithm for clustering large data sets with categorical values. Data Min Knowl Discov 2(3):283\u2013304","journal-title":"Data Min Knowl Discov"},{"issue":"1","key":"1674_CR30","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1108\/14691930310455414","volume":"4","author":"DP Hunt","year":"2003","unstructured":"Hunt DP (2003) The concept of knowledge and how to measure it. J intellect Cap 4(1):100\u2013113","journal-title":"J intellect Cap"},{"key":"1674_CR31","first-page":"88","volume":"125","author":"E Joseph","year":"2005","unstructured":"Joseph E (2005) Engagement tracing: using response times to model student disengagement. Artif Intell Educ Support Learn Intell Soc Inf Technol 125:88","journal-title":"Artif Intell Educ Support Learn Intell Soc Inf Technol"},{"key":"1674_CR32","unstructured":"Khalil F, Wang H, Li J (2007) Integrating Markov model with clustering for predicting web page accesses. In: Proceeding of the 13th Australasian world wide web conference (AusWeb07), AusWeb, pp 63\u201374"},{"issue":"1\u20132","key":"1674_CR33","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/s11257-010-9087-z","volume":"21","author":"M K\u00f6ck","year":"2011","unstructured":"K\u00f6ck M, Paramythis A (2011) Activity sequence modelling and dynamic clustering for personalized e-learning. User Model User Adapt Interact 21(1\u20132):51\u201397","journal-title":"User Model User Adapt Interact"},{"key":"1674_CR34","unstructured":"Lopez MI, Luna JM, Romero C, Ventura S (2012) Classification via clustering for predicting final marks based on student participation in forums. In: International educational data mining society"},{"issue":"1","key":"1674_CR35","first-page":"36","volume":"20","author":"J Magidson","year":"2002","unstructured":"Magidson J, Vermunt J (2002) Latent class models for clustering: a comparison with k-means. Can J Mark Res 20(1):36\u201343","journal-title":"Can J Mark Res"},{"key":"1674_CR36","doi-asserted-by":"crossref","unstructured":"Maqsood R, Ceravolo P (2018) Modeling behavioral dynamics in confidence-based assessment. In: 2018 IEEE 18th international conference on advanced learning technologies (ICALT). IEEE, pp 452\u2013454","DOI":"10.1109\/ICALT.2018.00112"},{"key":"1674_CR37","first-page":"55","volume-title":"Technology enhanced assessment 2018\u2013communications in computer and information science (CCIS)","author":"R Maqsood","year":"2019","unstructured":"Maqsood R, Ceravolo P (2019) Corrective feedback and its implications on students\u2019 confidence-based assessment. Technology enhanced assessment 2018\u2013communications in computer and information science (CCIS). Springer, Berlin, pp 55\u201372"},{"key":"1674_CR38","doi-asserted-by":"crossref","unstructured":"Maqsood R, Ceravolo P, Ventura S (2019) Discovering students\u2019 engagement behaviors in confidence-based assessment. In: 2019 IEEE global engineering education conference (EDUCON). IEEE, pp 841\u2013846","DOI":"10.1109\/EDUCON.2019.8725161"},{"key":"1674_CR39","doi-asserted-by":"crossref","unstructured":"Melnykov V (2016) Clickclust: an R package for model-based clustering of categorical sequences. J Stat Softw 74(i09)","DOI":"10.18637\/jss.v074.i09"},{"key":"1674_CR40","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1214\/09-SS053","volume":"4","author":"V Melnykov","year":"2010","unstructured":"Melnykov V, Maitra R et al (2010) Finite mixture models and model-based clustering. Stat Surv 4:80\u2013116","journal-title":"Stat Surv"},{"issue":"4","key":"1674_CR41","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1007\/s11634-016-0264-8","volume":"10","author":"S Michael","year":"2016","unstructured":"Michael S, Melnykov V (2016) An effective strategy for initializing the EM algorithm in finite mixture models. Adv Data Anal Classif 10(4):563\u2013583","journal-title":"Adv Data Anal Classif"},{"issue":"1\u20132","key":"1674_CR42","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/s11257-010-9086-0","volume":"21","author":"K Muldner","year":"2011","unstructured":"Muldner K, Burleson W, Van de Sande B, VanLehn K (2011) An analysis of students\u2019 gaming behaviors in an intelligent tutoring system: predictors and impacts. User Model User Adapt Interact 21(1\u20132):99\u2013135","journal-title":"User Model User Adapt Interact"},{"issue":"1","key":"1674_CR43","doi-asserted-by":"publisher","first-page":"107","DOI":"10.18608\/jla.2014.11.6","volume":"1","author":"ZA Pardos","year":"2014","unstructured":"Pardos ZA, Baker RS, San Pedro M et al (2014) Affective states and state tests: investigating how affect and engagement during the school year predict end-of-year learning outcomes. J Learn Anal 1(1):107\u2013128","journal-title":"J Learn Anal"},{"key":"1674_CR44","unstructured":"Park J, Yu R, Rodriguez F, et al (2018) Understanding student procrastination via mixture models. In: Proceedings of the 11th international conference on educational data mining (2018)"},{"issue":"3","key":"1674_CR45","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1007\/s11257-018-9204-y","volume":"28","author":"R Pel\u00e1nek","year":"2018","unstructured":"Pel\u00e1nek R (2018) The details matter: methodological nuances in the evaluation of student models. User Model User Adapt Interact 28(3):207\u2013235","journal-title":"User Model User Adapt Interact"},{"key":"1674_CR46","doi-asserted-by":"crossref","unstructured":"Petr DW (2000) Measuring (and enhancing?) student confidence with confidence scores. In: Frontiers in education conference, 2000. FIE 2000. 30th Annual, IEEE, vol\u00a01, pp T4B\u20131","DOI":"10.1109\/FIE.2000.897657"},{"issue":"1","key":"1674_CR47","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/MASSP.1986.1165342","volume":"3","author":"LR Rabiner","year":"1986","unstructured":"Rabiner LR, Juang BH (1986) An introduction to hidden Markov models. IEEE ASSP Mag 3(1):4\u201316","journal-title":"IEEE ASSP Mag"},{"issue":"5","key":"1674_CR48","doi-asserted-by":"publisher","first-page":"425","DOI":"10.1007\/s11257-004-7961-2","volume":"14","author":"C Romero","year":"2004","unstructured":"Romero C, Ventura S, De Bra P (2004) Knowledge discovery with genetic programming for providing feedback to courseware authors. User Model User Adapt Interact 14(5):425\u2013464","journal-title":"User Model User Adapt Interact"},{"issue":"3","key":"1674_CR49","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1023\/A:1009752403260","volume":"1","author":"SL Salzberg","year":"1997","unstructured":"Salzberg SL (1997) On comparing classifiers: pitfalls to avoid and a recommended approach. Data Min Knowl Discov 1(3):317\u2013328","journal-title":"Data Min Knowl Discov"},{"issue":"2","key":"1674_CR50","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1214\/aos\/1176344136","volume":"6","author":"G Schwarz","year":"1978","unstructured":"Schwarz G et al (1978) Estimating the dimension of a model. Ann Stat 6(2):461\u2013464","journal-title":"Ann Stat"},{"key":"1674_CR51","unstructured":"Tan L, Sun X, Khoo ST (2014) Can engagement be compared? Measuring academic engagement for comparison. In: EDM, pp 213\u2013216"},{"issue":"1","key":"1674_CR52","first-page":"93","volume":"21","author":"B Taraghi","year":"2015","unstructured":"Taraghi B, Saranti A, Ebner M et al (2015) Towards a learning-aware application guided by hierarchical classification of learner profiles. J UCS 21(1):93\u2013109","journal-title":"J UCS"},{"key":"1674_CR53","doi-asserted-by":"publisher","first-page":"771","DOI":"10.1007\/978-3-540-69132-7_104","volume-title":"Intelligent tutoring systems","author":"E Vasilyeva","year":"2008","unstructured":"Vasilyeva E, Pechenizkiy M, De Bra P (2008) Tailoring of feedback in web-based learning: the role of response certitude in the assessment. Intelligent tutoring systems. Springer, Berlin, pp 771\u2013773"},{"key":"1674_CR54","unstructured":"Vogt KL (2016) Measuring student engagement using learning management systems. PhD thesis, University of Toronto, Canada"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-022-01674-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10115-022-01674-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-022-01674-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T18:52:42Z","timestamp":1726944762000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10115-022-01674-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,7]]},"references-count":54,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2022,5]]}},"alternative-id":["1674"],"URL":"https:\/\/doi.org\/10.1007\/s10115-022-01674-9","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,7]]},"assertion":[{"value":"30 October 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 February 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 March 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 April 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}